code: def test_export_model_large(
      tmp_path,
      model_type,
      model_class,
      hf_pretrained_model_name_or_path,
  ):
      export_model(
          hf_pretrained_model_name_or_path=hf_pretrained_model_name_or_path,
          output_base_path=tmp_path,
      )
      read_config = py_io.read_json(
          os.path.join(tmp_path, f"config.json")
      )
      assert (
          read_config["hf_pretrained_model_name_or_path"]
          == hf_pretrained_model_name_or_path
      )
      assert read_config["model_path"] == os.path.join(
          tmp_path, "model", "model.p"
      )
      assert read_config["model_config_path"] == os.path.join(
          tmp_path, "model", "config.json"
      )
  
file_path: jiant/tests/proj/main/test_export_model.py
imports: import os
  import pytest
  from transformers import BertPreTrainedModel
  from transformers import BertTokenizer
  from transformers import DebertaV2ForMaskedLM
  from transformers import RobertaForMaskedLM
  from transformers import RobertaTokenizer
  import jiant.utils.python.io
  from jiant.proj.main.export_model import export_model
label_desc: Use image node_id 2 for calling a global function with example usage: test_export_model_large(tmp_path, model_type, model_class, hf_pretrained_model_name_or_path) without return types